CN110930988B - Method and system for determining phoneme score - Google Patents
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Abstract
The invention provides a method and a system for determining phoneme scores, wherein the method comprises the following steps: acquiring audio to be identified and a calibration text corresponding to the audio to be identified; performing voice recognition on the audio to be recognized, and acquiring recognition phonemes and first GOP scores corresponding to the recognition phonemes; determining whether the first GOP score is larger than or equal to a threshold score corresponding to the identified phoneme, wherein each phoneme is correspondingly provided with a threshold score; if the first GOP score is smaller than the threshold score, judging whether the identified phoneme is a competitive phoneme of the target phoneme; based on the determination result, a final GOP score is output. In the scheme, a corresponding threshold score is preset for each phoneme, a first GOP score corresponding to the identified phoneme is compared with the threshold score, and if the first GOP score is smaller than the threshold score, whether the identified phoneme is a competitive phoneme of the target phoneme is judged. And determining the final GOP scoring according to the judgment result, and improving the accuracy of phoneme scoring.
Description
Technical Field
The invention relates to the technical field of voice evaluation, in particular to a method and a system for determining phoneme scores.
Background
With the development of society, more and more people learn languages at present. When learning a language, a person usually assists learning by means of language learning software, for example, by scoring his own pronunciation by the language learning software and correcting the pronunciation according to the scoring result.
Current language learning software scores the user's pronunciation, typically using Goodness of pronunciations (GOPs). The specific scoring mode is as follows: the same threshold value is preset for all the phonemes, when a user uses language learning software, the GOP score of the target phoneme is calculated by using a GOP algorithm, and the GOP score and the threshold value are compared to determine whether the user pronounces accurately. But since many users pronounce unnormally and disorderly, different phonemes correspond to different Hidden Markov Model (HMMs) scores. The same threshold value is set for all phonemes, so that whether the pronunciation of the user is standard cannot be accurately judged, and the phoneme scoring accuracy is low.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and a system for determining a phoneme score, so as to solve the problems of low accuracy of phoneme score and the like in the existing phoneme scoring method.
In order to achieve the above purpose, the embodiments of the present invention provide the following technical solutions:
the first aspect of the embodiments of the present invention discloses a method for determining a phoneme score, where the method includes:
acquiring an audio to be recognized and a calibration text corresponding to the audio to be recognized, wherein the calibration text at least comprises a target phoneme;
performing voice recognition on the audio to be recognized, and acquiring a recognition phoneme and a first GOP score corresponding to the recognition phoneme;
determining whether the first GOP score is larger than or equal to a threshold score corresponding to the identified phoneme, wherein each phoneme is correspondingly provided with a threshold score;
if the first GOP score is smaller than the threshold score, judging whether the identified phoneme is a competitive phoneme of the target phoneme;
based on the determination result, a final GOP score is output.
Preferably, the outputting a final GOP score based on the judgment result includes:
if the judgment result is that the identified phoneme is not the competitive phoneme of the target phoneme, determining the first GOP score as a final GOP score;
and if the judgment result is that the identified phoneme is the competitive phoneme of the target phoneme, determining that a preset second GOP score corresponding to the target phoneme is a final GOP score.
Preferably, the process of setting a threshold score for each phoneme includes:
aiming at each phoneme, acquiring a plurality of historical GOP scores corresponding to the phoneme;
calculating a mean and variance of a plurality of historical GOP scores for the phoneme;
and determining the threshold score of the phoneme according to the average value and the variance.
Preferably, the judging whether the identified phoneme is a competitive phoneme of the target phoneme includes:
searching a competitive phoneme table based on the identification phoneme and the target phoneme, and judging whether the identification phoneme is a competitive phoneme of the target phoneme, wherein the competitive phoneme table is constructed in advance based on pronunciation similarity of the phonemes, and the competitive phoneme table at least comprises the target phoneme and the corresponding competitive phoneme.
Preferably, the method further comprises the following steps:
and if the first GOP score is larger than or equal to the threshold score, determining the first GOP score as a final GOP score.
The second aspect of the embodiments of the present invention discloses a system for determining phoneme scores, where the system includes:
the device comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring an audio to be identified and a calibration text corresponding to the audio to be identified, and the calibration text at least comprises a target phoneme;
the recognition unit is used for carrying out voice recognition on the audio to be recognized and acquiring a recognition phoneme and a first GOP score corresponding to the recognition phoneme;
the determining unit is used for determining whether the first GOP score is larger than or equal to a threshold score corresponding to the identified phoneme, a threshold score is set corresponding to each phoneme, and if the first GOP score is smaller than the threshold score, the judging unit is executed;
the judging unit is used for judging whether the recognition phoneme is a competitive phoneme of the target phoneme;
and the output unit is used for outputting the final GOP score based on the judgment result.
Preferably, the output unit is specifically configured to: and if the judgment result is that the identification phoneme is not the competitive phoneme of the target phoneme, determining that the first GOP score is the final GOP score, and if the judgment result is that the identification phoneme is the competitive phoneme of the target phoneme, determining that a preset second GOP score corresponding to the target phoneme is the final GOP score.
Preferably, the judging unit is specifically configured to: searching a competitive phoneme table based on the identification phoneme and the target phoneme, and judging whether the identification phoneme is a competitive phoneme of the target phoneme, wherein the competitive phoneme table is constructed in advance based on pronunciation similarity of the phonemes, and the competitive phoneme table at least comprises the target phoneme and the corresponding competitive phoneme.
The third aspect of the embodiments of the present invention discloses an electronic device, where the electronic device is configured to run a program, where the program executes the method for determining a phoneme score as disclosed in the first aspect of the embodiments of the present invention when running.
A fourth aspect of the embodiments of the present invention discloses a storage medium, where the storage medium includes a stored program, and when the program runs, a device in which the storage medium is located is controlled to execute the method for determining a phoneme score as disclosed in the first aspect of the embodiments of the present invention.
Based on the above method and system for determining phoneme scores provided by the embodiments of the present invention, the method includes: acquiring audio to be identified and a calibration text corresponding to the audio to be identified; performing voice recognition on the audio to be recognized, and acquiring recognition phonemes and first GOP scores corresponding to the recognition phonemes; determining whether the first GOP score is larger than or equal to a threshold score corresponding to the identified phoneme, wherein each phoneme is correspondingly provided with a threshold score; if the first GOP score is smaller than the threshold score, judging whether the identified phoneme is a competitive phoneme of the target phoneme; based on the determination result, a final GOP score is output. In the scheme, a corresponding threshold score is preset for each phoneme, and the audio to be recognized is subjected to voice recognition to obtain a recognized phoneme and a first GOP score. And if the first GOP score is smaller than the threshold score corresponding to the identification phoneme, judging whether the identification phoneme is a competitive phoneme of the target phoneme, and outputting a final GOP score based on a judgment result. And comparing the first GOP score with a threshold score corresponding to the identified phoneme, and judging whether the identified phoneme is a competitive phoneme of the target phoneme, so as to determine a final GOP score and improve the accuracy of the phoneme score.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a flowchart of a method for determining a phoneme score according to an embodiment of the present invention;
FIG. 2 is a flow chart of setting a threshold score according to an embodiment of the present invention;
FIG. 3 is a flow chart of another method for determining phoneme scores according to an embodiment of the present invention;
fig. 4 is a block diagram illustrating a structure of a system for determining a phoneme score according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In this application, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
As known in the background art, the current phoneme scoring method is as follows: setting the same threshold value for all phonemes in advance, calculating the GOP score of the target phoneme by using a GOP algorithm, and comparing the GOP score with the threshold value to determine whether the pronunciation of the user is accurate. However, since many users pronounce unnormally and disorderly, different phones correspond to different HMMs scores. The same threshold value is set for all phonemes, so that whether the pronunciation of the user is standard cannot be accurately judged, and the phoneme scoring accuracy is low.
Therefore, embodiments of the present invention provide a method and a system for determining a phoneme score, where a corresponding threshold score is preset for each phoneme, a first GOP score of an identified phoneme is compared with the threshold score, and if the first GOP score is smaller than the threshold score, it is determined whether the identified phoneme is a competitive phoneme of a target phoneme. And determining the final GOP score according to the judgment result so as to improve the accuracy of the phoneme score.
Referring to fig. 1, a flowchart of a method for determining a phoneme score according to an embodiment of the present invention is shown, where the method for determining a phoneme score includes the following steps:
step S101: and acquiring the audio to be recognized and a calibration text corresponding to the audio to be recognized.
In the process of specifically implementing step S101, the target phoneme is included in the calibration text, and it can be understood that the target phoneme refers to: phonemes a user is read during the learning of a language.
For example: when a user learns English, learning software shows phonemes to the user
I.e. the user needs to read the phoneme aloud. The speech read by the user is the audio to be identified, and the target phoneme is the phoneme read by the user
。
It should be noted that, in the above example, the user only reads one phoneme, the english word is composed of more than one phoneme, and the user may read one english word or read multiple english words in the process of actually learning english. The method comprises the steps of splitting the content read by a user into single phonemes, wherein a target phoneme is a phoneme forming a read English word, and scoring the pronunciation of the user by combining the pronunciation of each phoneme of the user.
It should be further noted that the language learned by the user is not limited to english, and the content of determining the phoneme score according to the embodiment of the present invention is also applicable to other languages.
Step S102: and performing voice recognition on the audio to be recognized, and acquiring the recognition phonemes and the first GOP scores corresponding to the recognition phonemes.
In the process of implementing step S102 specifically, the content in the audio to be recognized is subjected to speech recognition, and phonemes in the audio to be recognized are recognized, so as to obtain recognized phonemes and a first GOP score corresponding to the recognized phonemes.
Step S103: it is determined whether the first GOP score is greater than or equal to a threshold score corresponding to the identified phoneme. If the first GOP score is greater than or equal to the threshold score, step S104 is executed, and if the first GOP score is less than the threshold score, step S105 is executed.
A threshold score is set in advance for each phoneme, that is, a threshold score corresponding to the phoneme itself is identified. In the process of implementing step S103 specifically, the first GOP score of the identified phoneme is compared with the threshold score. And if the first GOP score is larger than or equal to the threshold score, determining the first GOP score as a final GOP score. And if the first GOP score is smaller than the threshold score, judging whether the identified phoneme is a competitive phoneme of the target phoneme.
When the first GOP score is greater than or equal to the threshold score, the following two cases exist:
the first case is: and the recognition phoneme is consistent with the target phoneme, namely the recognition phoneme obtained by recognizing the audio to be recognized is consistent with the target phoneme in the calibration text, the pronunciation standard of the user is indicated and accurate, and the first GOP score is determined as the final GOP score.
The second case is: the recognition phoneme is inconsistent with the target phoneme, namely the recognition phoneme obtained by recognizing the audio to be recognized is not the target phoneme in the calibration text, namely the pronunciation of the user is inaccurate, and the target phoneme is read into other phonemes. But since the first GOP score is greater than or equal to the threshold score corresponding to the recognized phoneme, indicating the pronunciation criteria of the user, the first GOP score is determined to be the final GOP score.
Step S104: the first GOP score is determined to be the final GOP score.
Step S105: and judging whether the identified phoneme is a competitive phoneme of the target phoneme.
It should be noted that users in different regions have different pronunciation characteristics when learning a language, pronunciation data of a large number of users in a preset region when learning the language is collected in advance, the collected pronunciation data is analyzed, pronunciation similarity between phonemes corresponding to the language is determined, and a competitive phoneme table is constructed based on the pronunciation similarity of the phonemes. That is to say, according to the pronunciation characteristics of the user to different phonemes in the preset region, the pronunciation similarity between the phonemes is determined, so that the constructed competitive phoneme table is closer to the actual use condition of the user in the preset region.
For example: collecting pronunciation data of a large number of Chinese users when learning English, analyzing the large number of pronunciation data, and counting pronunciation similarity of the Chinese users to 48 phonemes in the English so as to construct a competitive phoneme table. The constructed competitive phoneme table is closer to the actual use condition of Chinese users.
In the process of implementing step S105 specifically, a competitive phoneme table is searched based on the recognition phoneme and the target phoneme, and it is determined whether the recognition phoneme is a competitive phoneme of the target phoneme, where the competitive phoneme table at least includes the target phoneme and the corresponding competitive phoneme.
It should be noted that each phoneme and the corresponding competitive phoneme are included in the competitive phoneme table, and the following contents are exemplified to better explain the contents of the competitive phoneme table.
Analyzing pronunciation characteristics of 48 phonemes in English of a large number of Chinese users, and constructing a competitive phoneme table according to an analysis result, wherein the following contents are part of contents of the competitive phoneme table, and correspondingly, the following contents of the competitive phoneme table are only used for illustration.
Competitive phoneme table:
aa ═ aa | ah | er | ao, i.e., competing phonemes indicating the phoneme "aa" are: "aa", "ah", "er" and "ao". Other contents of the competitive phoneme table can be found, and are not described in detail herein.
It should be noted that, the competitive phoneme table is stored in a specific file, for example: the competitive phoneme table is stored into the neighbors configuration file.
Step S106: based on the determination result, a final GOP score is output.
In the process of implementing step S106 specifically, the determination result is a competitive phoneme whose identified phoneme is not the target phoneme, or the determination result is a competitive phoneme whose identified phoneme is the target phoneme.
And if the judgment result is that the identified phoneme is not the competitive phoneme of the target phoneme, determining the first GOP score as the final GOP score.
And if the judgment result is that the identified phoneme is the competitive phoneme of the target phoneme, determining a preset second GOP score corresponding to the target phoneme as a final GOP score. It should be noted that, a corresponding second GOP score is set for the target phoneme in advance.
In the embodiment of the invention, a competitive phoneme table is constructed in advance, and a corresponding threshold score is set for each phoneme. And carrying out voice recognition on the audio to be recognized to obtain a recognition phoneme and a first GOP score. If the first GOP score is smaller than the threshold score corresponding to the identified phoneme, judging whether the identified phoneme is a competitive phoneme of the target phoneme by using a competitive phoneme table, outputting a final GOP score based on a judgment result, and improving the accuracy of the phoneme score.
In the above-mentioned embodiment of the present invention, referring to fig. 2, the process of setting a threshold score for each phoneme related to step S103 in fig. 1 is shown as a flowchart for setting a threshold score, which includes the following steps:
step S201: and acquiring a plurality of historical GOP scores corresponding to the phonemes aiming at each phoneme.
In the process of implementing step S201, for each phoneme, a large number of historical GOP scores corresponding to the phoneme are collected. That is, the threshold score of each phoneme needs to be determined based on a large number of historical GOP scores of the phoneme, i.e., there is a respective threshold score for each phoneme, rather than one threshold score common to all phonemes.
Step S202: the mean and variance of the multiple historical GOP scores for the phoneme are calculated.
In the process of implementing step S202, for each phoneme, the average and variance of the collected multiple historical GOP scores of the phoneme are calculated.
Step S203: and determining the threshold score of the phoneme according to the average value and the variance.
In a specific implementation, for each phoneme, the threshold score T of the phoneme is calculated by formula (1) using the mean and variance corresponding to the phoneme calculated in step S202q。
Tq＝uq+aσq+β (1)
In formula (1), q denotes each phoneme, uqIs the mean value, σqFor variance, a and β are preset coefficients, such as: a is more than 0.8 and less than 1.3, and beta is more than 1.0 and less than-2.0.
In the embodiment of the invention, a plurality of historical GOP scores of each phoneme are collected in advance, and the threshold score of the phoneme is determined by using the plurality of historical GOP scores corresponding to each phoneme, so that the obtained threshold score is more suitable for the phoneme corresponding to the threshold score. Each phoneme corresponds to one threshold score, and all phonemes do not share one threshold score, so that the accuracy of phoneme scoring is improved.
To better explain the contents shown in fig. 1 of the above embodiment of the present invention, fig. 3 is used for illustration, and it should be noted that fig. 3 is used for illustration only.
Referring to fig. 3, a flowchart of another method for determining a phoneme score according to an embodiment of the present invention is shown, which includes the following steps:
step S301: and acquiring the audio to be recognized and the calibration text.
In the process of implementing step S301, the specific contents of the audio to be recognized and the calibration text may refer to the contents shown in step S101 in fig. 1 in the above embodiment of the present invention.
Step S302: and performing voice recognition on the audio to be recognized, and acquiring the recognition phonemes and the first GOP scores corresponding to the recognition phonemes.
In the process of implementing step S302 specifically, speech recognition is performed on the audio to be recognized, and the phoneme with the highest recognition probability in the audio to be recognized is determined as the recognition phoneme.
Step S303: it is determined whether the first GOP score is greater than or equal to a threshold score for identifying the phoneme. If the first GOP score is greater than or equal to the threshold score of the identified phoneme, step S304 is executed, and if the first GOP score is less than the threshold score of the identified phoneme, step S305 is executed.
In the process of implementing step S303 specifically, the threshold score of each phoneme is set, as described in fig. 2 in the above embodiment of the present invention.
Step S304: the first GOP score is determined to be the final GOP score.
Step S305: and judging whether the identified phoneme is a competitive phoneme of the target phoneme. If the identified phoneme is the competitive phoneme of the target phoneme, step S306 is executed, and if the identified phoneme is not the competitive phoneme of the target phoneme, step S307 is executed.
In the process of implementing step S305 specifically, the process of determining whether the phoneme identified is a competitive phoneme of the target phoneme is described in the above embodiment of the present invention in step S105 of fig. 1.
Step S306: and determining a second GOP score corresponding to the target phoneme as a final GOP score.
Step S307: the first GOP score is determined to be the final GOP score.
In the embodiment of the invention, a competitive phoneme table is constructed in advance, and a corresponding threshold score is set for each phoneme. And carrying out voice recognition on the audio to be recognized to obtain a recognition phoneme and a first GOP score. If the first GOP score is smaller than the threshold score corresponding to the identified phoneme, judging whether the identified phoneme is a competitive phoneme of the target phoneme by using a competitive phoneme table, outputting a final GOP score based on a judgment result, and improving the accuracy of the phoneme score.
Corresponding to the method for determining a phoneme score provided in the embodiment of the present invention, referring to fig. 4, a block diagram of a system for determining a phoneme score is further provided in the embodiment of the present invention, where the system for determining a phoneme score includes: an acquisition unit 401, a recognition unit 402, a determination unit 403, a judgment unit 404, and an output unit 405.
The obtaining unit 401 is configured to obtain an audio to be recognized and a calibration text corresponding to the audio to be recognized, where the calibration text at least includes a target phoneme.
The recognition unit 402 is configured to perform speech recognition on the audio to be recognized, and acquire a recognition phoneme and a first GOP score corresponding to the recognition phoneme.
The determining unit 403 is configured to determine whether the first GOP score is greater than or equal to a threshold score corresponding to the identified phoneme, where each phoneme is provided with a threshold score, and if the first GOP score is less than the threshold score, execute the determining unit 404.
Preferably, if the first GOP score is greater than or equal to the threshold score, the determining unit 403 is further configured to: the first GOP score is determined to be the final GOP score.
A judging unit 404, configured to judge whether the identified phoneme is a competitive phoneme of the target phoneme.
In a specific implementation, the determining unit 404 is specifically configured to: and searching a competitive phoneme table based on the recognition phoneme and the target phoneme, and judging whether the recognition phoneme is a competitive phoneme of the target phoneme, wherein the competitive phoneme table is constructed in advance based on pronunciation similarity of the phonemes, and the competitive phoneme table at least comprises the target phoneme and the corresponding competitive phoneme.
An output unit 405, configured to output the final GOP score based on the determination result.
In a specific implementation, the output unit 405 is specifically configured to: and if the judgment result is that the identified phoneme is not the competitive phoneme of the target phoneme, determining that the first GOP score is the final GOP score, and if the judgment result is that the identified phoneme is the competitive phoneme of the target phoneme, determining that a preset second GOP score corresponding to the target phoneme is the final GOP score.
In the embodiment of the invention, a competitive phoneme table is constructed in advance, and a corresponding threshold score is set for each phoneme. And carrying out voice recognition on the audio to be recognized to obtain a recognition phoneme and a first GOP score. If the first GOP score is smaller than the threshold score corresponding to the identified phoneme, judging whether the identified phoneme is a competitive phoneme of the target phoneme by using a competitive phoneme table, outputting a final GOP score based on a judgment result, and improving the accuracy of the phoneme score.
Preferably, in conjunction with the content shown in fig. 4, the determining unit 403 includes: the device comprises an acquisition module, a calculation module and a determination module, wherein the execution principle of each module is as follows:
and the acquisition module is used for acquiring a plurality of historical GOP scores corresponding to the phonemes aiming at each phoneme.
A calculation module to calculate a mean and variance of the plurality of historical GOP scores for the phoneme.
And the determining module is used for determining the threshold score of the phoneme according to the average value and the variance.
In the embodiment of the invention, a plurality of historical GOP scores of each phoneme are collected in advance, and the threshold score of the phoneme is determined by using the plurality of historical GOP scores corresponding to each phoneme, so that the obtained threshold score is more suitable for the phoneme corresponding to the threshold score. Each phoneme corresponds to one threshold score, and all phonemes do not share one threshold score, so that the accuracy of phoneme scoring is improved.
Based on the system for determining phoneme scores disclosed in the embodiment of the present invention, the modules may be implemented by an electronic device including a processor and a memory. The method specifically comprises the following steps: the modules are stored in a memory as program units, and the program units stored in the memory are executed by a processor to realize phoneme scoring.
The processor comprises a kernel, and the kernel calls a corresponding program unit from the memory. The kernel can be set to one or more, and phoneme scoring is realized by adjusting kernel parameters.
The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.
Further, an embodiment of the present invention provides a processor, where the processor is configured to execute a program, where the program executes a method for determining a phoneme score.
Further, an embodiment of the present invention provides an electronic device, which includes a processor, a memory, and a program stored in the memory and running on the processor, and when the processor executes the program, the processor implements the method for determining the phoneme score as shown in any of the above embodiments.
The equipment disclosed in the embodiment of the invention can be a PC, a PAD, a mobile phone and the like.
Further, an embodiment of the present invention also provides a storage medium having a program stored thereon, where the program is executed by a processor to implement phoneme scoring.
The present application further provides a computer program product adapted to perform a determination method of initializing a phoneme score as shown in any of the embodiments above when executed on a data processing device.
In summary, an embodiment of the present invention provides a method and a system for determining a phoneme score, where the method includes: acquiring audio to be identified and a calibration text corresponding to the audio to be identified; performing voice recognition on the audio to be recognized, and acquiring recognition phonemes and first GOP scores corresponding to the recognition phonemes; determining whether the first GOP score is larger than or equal to a threshold score corresponding to the identified phoneme, wherein each phoneme is correspondingly provided with a threshold score; if the first GOP score is smaller than the threshold score, judging whether the identified phoneme is a competitive phoneme of the target phoneme; based on the determination result, a final GOP score is output. In the scheme, a corresponding threshold score is preset for each phoneme, and the audio to be recognized is subjected to voice recognition to obtain a recognized phoneme and a first GOP score. And if the first GOP score is smaller than the threshold score corresponding to the identification phoneme, judging whether the identification phoneme is a competitive phoneme of the target phoneme, and outputting a final GOP score based on a judgment result. And comparing the first GOP score with a threshold score corresponding to the identified phoneme, and judging whether the identified phoneme is a competitive phoneme of the target phoneme, so as to determine a final GOP score and improve the accuracy of the phoneme score.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the system or system embodiments are substantially similar to the method embodiments and therefore are described in a relatively simple manner, and reference may be made to some of the descriptions of the method embodiments for related points. The above-described system and system embodiments are only illustrative, wherein the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method for determining a phoneme score, the method comprising:
acquiring an audio to be recognized and a calibration text corresponding to the audio to be recognized, wherein the calibration text at least comprises a target phoneme;
performing voice recognition on the audio to be recognized, and acquiring a recognition phoneme and a first GOP score corresponding to the recognition phoneme;
determining whether the first GOP score is larger than or equal to a threshold score corresponding to the identified phoneme, wherein each phoneme is correspondingly provided with a threshold score;
if the first GOP score is smaller than the threshold score, judging whether the identified phoneme is a competitive phoneme of the target phoneme;
based on the determination result, a final GOP score is output.
2. The method of claim 1, wherein outputting a final GOP score based on the determination comprises:
if the judgment result is that the identified phoneme is not the competitive phoneme of the target phoneme, determining the first GOP score as a final GOP score;
and if the judgment result is that the identified phoneme is the competitive phoneme of the target phoneme, determining that a preset second GOP score corresponding to the target phoneme is a final GOP score.
3. The method of claim 1, wherein the process of setting a threshold score for each phoneme comprises:
aiming at each phoneme, acquiring a plurality of historical GOP scores corresponding to the phoneme;
calculating a mean and variance of a plurality of historical GOP scores for the phoneme;
and determining the threshold score of the phoneme according to the average value and the variance.
4. The method of claim 1, wherein said determining whether said identified phoneme is a competing phoneme of said target phoneme comprises:
searching a competitive phoneme table based on the identification phoneme and the target phoneme, and judging whether the identification phoneme is a competitive phoneme of the target phoneme, wherein the competitive phoneme table is constructed in advance based on pronunciation similarity of the phonemes, and the competitive phoneme table at least comprises the target phoneme and the corresponding competitive phoneme.
5. The method of claim 1, further comprising:
and if the first GOP score is larger than or equal to the threshold score, determining the first GOP score as a final GOP score.
6. A system for phoneme scoring, the system comprising:
the device comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring an audio to be identified and a calibration text corresponding to the audio to be identified, and the calibration text at least comprises a target phoneme;
the recognition unit is used for carrying out voice recognition on the audio to be recognized and acquiring a recognition phoneme and a first GOP score corresponding to the recognition phoneme;
the determining unit is used for determining whether the first GOP score is larger than or equal to a threshold score corresponding to the identified phoneme, a threshold score is set corresponding to each phoneme, and if the first GOP score is smaller than the threshold score, the judging unit is executed;
the judging unit is used for judging whether the recognition phoneme is a competitive phoneme of the target phoneme;
and the output unit is used for outputting the final GOP score based on the judgment result.
7. The system of claim 6, wherein the output unit is specifically configured to: and if the judgment result is that the identification phoneme is not the competitive phoneme of the target phoneme, determining that the first GOP score is the final GOP score, and if the judgment result is that the identification phoneme is the competitive phoneme of the target phoneme, determining that a preset second GOP score corresponding to the target phoneme is the final GOP score.
8. The system according to claim 6, wherein the determining unit is specifically configured to: searching a competitive phoneme table based on the identification phoneme and the target phoneme, and judging whether the identification phoneme is a competitive phoneme of the target phoneme, wherein the competitive phoneme table is constructed in advance based on pronunciation similarity of the phonemes, and the competitive phoneme table at least comprises the target phoneme and the corresponding competitive phoneme.
9. An electronic device, characterized in that the electronic device is adapted to run a program, wherein the program when running performs the method of phoneme scoring as claimed in any one of claims 1 to 5.
10. A storage medium comprising a stored program, wherein the program, when executed, controls a device on which the storage medium is located to perform a phoneme score determination method according to any one of claims 1 to 5.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6711541B1 (en) * | 1999-09-07 | 2004-03-23 | Matsushita Electric Industrial Co., Ltd. | Technique for developing discriminative sound units for speech recognition and allophone modeling |
| CN101727903A (en) * | 2008-10-29 | 2010-06-09 | 中国科学院自动化研究所 | Pronunciation quality assessment and error detection method based on fusion of multiple characteristics and multiple systems |
| EP2450877B1 (en) * | 2010-11-09 | 2013-04-24 | Sony Computer Entertainment Europe Limited | System and method of speech evaluation |
| CN109979433A (en) * | 2019-04-02 | 2019-07-05 | 北京儒博科技有限公司 | Voice is with reading processing method, device, equipment and storage medium |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7409345B2 (en) * | 2003-04-04 | 2008-08-05 | International Business Machines Corporation | Methods for reducing spurious insertions in speech recognition |
| GB0426347D0 (en) * | 2004-12-01 | 2005-01-05 | Ibm | Methods, apparatus and computer programs for automatic speech recognition |
| CN101105939B (en) * | 2007-09-04 | 2012-07-18 | 安徽科大讯飞信息科技股份有限公司 | Sonification guiding method |
| US20110184723A1 (en) * | 2010-01-25 | 2011-07-28 | Microsoft Corporation | Phonetic suggestion engine |
| US9741339B2 (en) * | 2013-06-28 | 2017-08-22 | Google Inc. | Data driven word pronunciation learning and scoring with crowd sourcing based on the word's phonemes pronunciation scores |
| CN104952444B (en) * | 2015-04-27 | 2018-07-17 | 桂林电子科技大学 | A kind of Chinese's Oral English Practice method for evaluating quality that text is unrelated |
| CN109545244A (en) * | 2019-01-29 | 2019-03-29 | 北京猎户星空科技有限公司 | Speech evaluating method, device, electronic equipment and storage medium |
| CN109712643A (en) * | 2019-03-13 | 2019-05-03 | 北京精鸿软件科技有限公司 | The method and apparatus of Speech Assessment |
| CN110136747A (en) * | 2019-05-16 | 2019-08-16 | 上海流利说信息技术有限公司 | A kind of method, apparatus, equipment and storage medium for evaluating phoneme of speech sound correctness |
-
2019
- 2019-12-13 CN CN201911284482.7A patent/CN110930988B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6711541B1 (en) * | 1999-09-07 | 2004-03-23 | Matsushita Electric Industrial Co., Ltd. | Technique for developing discriminative sound units for speech recognition and allophone modeling |
| CN101727903A (en) * | 2008-10-29 | 2010-06-09 | 中国科学院自动化研究所 | Pronunciation quality assessment and error detection method based on fusion of multiple characteristics and multiple systems |
| EP2450877B1 (en) * | 2010-11-09 | 2013-04-24 | Sony Computer Entertainment Europe Limited | System and method of speech evaluation |
| CN109979433A (en) * | 2019-04-02 | 2019-07-05 | 北京儒博科技有限公司 | Voice is with reading processing method, device, equipment and storage medium |
Non-Patent Citations (2)
| Title |
|---|
| Phoneme and Word Scoring in Speech-in-Noise Audiometry;Curtis J. Billings et al;《American Journal of Audiology》;20160331;第25卷;全文 * |
| 英文发音中错误语音自动识别系统设计;王兴刚;《现代电子技术》;20180515;第41卷(第10期);全文 * |
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